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Detecting lags in nonlinear time series with PROC TSSELECTLAG in SAS Viya - The SAS Data Science Blog
Accurately identifying lag structures between related time series is essential in public health forecasting, particularly during epidemics where delays between infections and hospitalizations affect planning. Using a simulated SEIR model and SAS Viya’s PROC TSSELECTLAG, distance correlation is shown to outperform Pearson correlation by correctly identifying nonlinear lag relationships—such as the true seven-day lag between new infections and hospital admissions.
Threat modeling for agentic systems - The SAS Data Science Blog
As agentic AI systems evolve through protocols like MCP and A2A, traditional security practices must be adapted to address new risks such as goal misalignment and tool instruction abuse. This article explores practical threat modeling strategies, including goal alignment cascades and distinguishing between parameter-only vs. instruction-enabled tool calls.
Training Code, Scoring Code, and What Makes a Model - The SAS Data Science Blog
In a previous article, I wrote about a mistake I made as a student in analytics. In short, my team handed off our training code and training data as the deliverable for our Capstone project, citing that the users can rerun our training code to get the model.
Leveraging the long-tailed nature of power outage impacts as a targeted approach for condition-based maintenance of the overhead distribution grid - The SAS Data Science Blog
As described in our T&D World Article, SAS and our partner Exacter Inc. are helping utilities shift maintenance away from this reactive system towards a more efficient framework of condition-based maintenance (CBM).
How to handle RSVP ‘maybe’s’ - The SAS Data Science Blog
They say nothing in life is certain other than death and taxes, but there something else I’ve found I can count on from experience: sending out invites for a party on social media only to receive a few affirmative responses and a whole slew of “maybe”.
Unveiling Oceanus: Harnessing SAS Visual Analytics to combat illegal fishing networks - The SAS Data Science Blog
As part of this year's IEEE Visual Analytics Science and Technology (VAST) Challenge, a group of SAS data scientists puit SAS Viya and related machine learning tools to the ultimate test - to identify individuals in a complex fishing network. Excitedly, the team received the Honorable Mention Award for Breadth of Investigation!
A Nutrition Label for AI Models: SAS Model Cards Now Available - The SAS Data Science Blog
What sets the SAS Model Card apart from previous model cards is the use of descriptive visuals, to make model cards accessible to all personas involved in the analytics process, including data scientists, data engineers, MLOPs engineers, managers, executives, risk managers, business analytics, end-users, and any other stakeholder with access to the SAS Viya environment.
Integrating SAS and Python: An intern's journey of growth - The SAS Data Science Blog
Learn how an intern integrated SAS Viya® and open-source code (Python) into a Machine Learning project to combine their strengths within the context of predictive modeling, and to show off the variety of ways this integration can be accomplished.
The Ultimate Must-Have for MLOps: SAS Viya - The SAS Data Science Blog
A recent article came out with an updated list of necessary components for MLOps and LLMOps. And while this list may seem long, reading through the capabilities and components, I realized that SAS Viya already covers most of the required functionality. Organizations can have a hodgepodge of tools that they
Natural Language Processing techniques that improve data quality with LLMs - The SAS Data Science Blog
Adding linguistic techniques in SAS NLP with LLMs not only help address quality issues in text data, but since they can incorporate subject matter expertise, they give organizations a tremendous amount of control over their corpora.
Identifying time delays in batch manufacturing for accurate anomaly detection - The SAS Data Science Blog
Batch manufacturing involves producing goods in batches rather than in a continuous stream. This approach is common in industries such as pharmaceuticals, chemicals, and materials processing, where precise control over the production process is essential to ensure product quality and consistency. One critical aspect of batch manufacturing is the need to manage and understand inherent time delays that occur at various stages of the process.
How to manage and govern prompts of Large Language Models with SAS - The SAS Data Science Blog
SAS Viya can allow users and organizations to more easily interface with the LLM application, build better prompts and evaluate systematically which of these prompts leads to the best responses to ensure the best outcomes.
Planning your solar eclipse journey with network analytics - The SAS Data Science Blog
Authors: Steven Harenberg and Amy Becker The total solar eclipse taking place across a thin band of the United States on April 8, 2024, is going to be a stellar event. In this post, we will help plan a journey to see the total solar eclipse. We will use algorithms